Resilience Modeling of Power Systems under Various Hazards Considering Aging and Overloading Effects

The high intensity and frequency of extreme weather events in recent years raised the importance and need for resilient power systems. In addition to the effects of the unavoidable conditions such as aging and overloading, such events provide major threats to the reliability and stability of electrical grids. As a result, modeling components failure rate and repair time as time-varying parameter depending on the the component's age, loading condition and weather conditions is crucial to effectively mitigate the impacts of these disruptions. This paper proposes an accurate model that integrates these factors into a unified framework for assessing power system resilience. Based on the time-varying failure rate and repair time, the framework uses sequential Monte Carlo simulation and the Expected Energy Not Supplied (EENS) index under different operational scenarios to evaluate the resilience of the system. The proposed model and assessment method were applied on the single-area IEEE Reliability Test System (RTS), utilizing detailed data to simulate the effects of aging and extreme weather events on overhead transmission lines. The results highlight the model's ability to accurately represent the dynamic nature of component failure rates and offer insightful information for assessing and improving power systems' resilience.